The objective of this work is to develop a simulation approach to predict deep bed hop drying under different air temperature and velocity scenarios. Promising results will be used to guide future experimental efforts. A discretized deep bed hop drying model was developed by using multiple thin layer models built using the lumped reaction engineering approach to predict drying behavior in each bed layer. The reaction engineering approach was modified by introducing a specific surface area parameter to simplify the modeling of the complex and variable hop geometry, with an average percent error of 12.7%. The model was used to calculate drying time, thermal efficiency and moisture stratification for different drying scenarios: (1) constant air inlet temperature and velocity, (2) an initially elevated air temperature, and (3) drying with variable air temperature and velocity combinations. The initially elevated temperature had the shortest drying times with similar thermal efficiency to drying with a constant air temperature. Reducing the air velocity in the later drying stages resulted in the highest thermal efficiency but the longest batch time. In general, shorter drying times were more energy intensive.